Rosenkranz H S, Klopman G
Department of Environmental Health Sciences, Case Western Reserve University, Cleveland, OH 44106.
Mutat Res. 1990 Oct;232(2):249-60. doi: 10.1016/0027-5107(90)90131-m.
The CASE structure-activity relational method was applied to the model polyfunctional electrophile proposed by Ashby and associates. The predicted activities from data bases of 'structural alerts', mutagenicity in Salmonella and rodent carcinogenicity were compared. It was thus found that the predictive efficacy of CASE was increased when it employed a combination of human and artificial intelligence, as exemplified by the CASE analysis of 'structural alerts.
CASE结构-活性关系方法应用于阿什比及其同事提出的模型多官能亲电试剂。比较了“结构警示”数据库、沙门氏菌致突变性和啮齿动物致癌性数据的预测活性。结果发现，当CASE采用人工智能与人类智能相结合的方式时，其预测效果会提高，如“结构警示”的CASE分析所示。
